Transforming complex data into actionable insights and elegant visualizations
I'm a data scientist and analyst passionate about transforming data into valuable insights. With expertise in statistical analysis, machine learning, and data visualization, I help organizations make data-driven decisions.
My approach combines technical expertise with strong communication skills to translate complex findings into clear, actionable recommendations. I'm constantly exploring new technologies and methodologies to enhance my analytical capabilities.
Detects and visualizes trending news topics by clustering semantically similar articles. Uses MiniLM for embeddings, Facebook BART for summarization, and UMAP for dimensionality reduction.
Built an interactive Power BI dashboard to analyze employee attrition across roles, age groups, education, salary, and experience. Identified key drivers of attrition including low salary (under $5K), age group 26–35, and job roles like Laboratory Technician and Sales Executive. Enabled HR teams to make data-driven retention strategies.
Performed association rule mining on transaction data to identify product affinities and optimize store layouts.
Developed a machine learning pipeline to predict asthma risk based on patient demographic and clinical data. Performed extensive preprocessing, feature selection (Boruta, LDA, Random Forest), and balanced the dataset using undersampling techniques. Evaluated models like XGBoost, SVM, and AdaBoost using AUC and MCC for reliable classification.
Published a report to highlight the ESG risks of floods in flood prone areas using Satellite Imagery, Geospatial Analysis and Deep Learning.
Built an end-to-end wound analysis system using a fine-tuned DeepLabv3 model for segmentation. Integrated real-time image processing via Apache Kafka and Flask API. Supports RGB input and outputs segmentation masks for clinical assessment
GPA: 3.93 / 4.00
GPA: 8.90 / 10
Interested in working together or have questions about my projects? Feel free to reach out!